An Efficient Optimization Algorithm for Measurement Matrix Based on SVD and Improved Nesterov Accelerated Gradient

Simple item page
dc.contributor.authorZhang, B.
dc.contributor.authorYi, R.
dc.contributor.authorWang, Z.
dc.contributor.authorPu, J.
dc.contributor.authorSun, Y.
dc.coverage.issue2cs
dc.coverage.volume34cs
dc.date.accessioned2025-05-12T08:56:25Z
dc.date.available2025-05-12T08:56:25Z
dc.date.issued2025-06cs
dc.description.abstractIn compressed sensing, a measurement matrix having low coherence with a specified sparse dictionary has been shown to be advantageous over a Gaussian random matrix in terms of reconstruction performance. In this paper the problem of efficiently designing the measurement matrix is addressed. The measurement matrix is designed by iteratively minimizing the difference between the Gram matrix of the sensing matrix and a target Gram matrix. A new target Gram matrix is designed by applying singular value decomposition to the sensing matrix and utilizing entry shrinking in the Gram matrix, leading to lower mutual coherence indicators. An improved Nesterov accelerated gradient algorithm is derived to update the measurement matrix, which can improve the convergence behavior. An efficient optimization algorithm for measurement matrix is proposed on the basis of alternating minimization. The experimental results and analysis show that the proposed algorithm performs well in terms of both computational complexity and reconstruction performance.en
dc.formattextcs
dc.format.extent234-242cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2025 vol. 34, č. 2, s. 234-242. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2025.0234en
dc.identifier.issn1210-2512
dc.identifier.urihttps://hdl.handle.net/11012/250917
dc.language.isoencs
dc.publisherRadioengineering Societycs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2025/25_02_0234_0242.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectCompressed sensingen
dc.subjectequiangular tight frameen
dc.subjectsingular value decompositionen
dc.subjectmutual coherenceen
dc.subjectNesterov accelerated gradienten
dc.titleAn Efficient Optimization Algorithm for Measurement Matrix Based on SVD and Improved Nesterov Accelerated Gradienten
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
25_02_0234_0242.pdf
Size:
1008.38 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
2025/2